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Inducing truthful revelation of generator reliability

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  • Devine, Mel T.
  • Lynch, Muireann Á.

Abstract

Liberalised electricity markets often include a capacity remuneration mechanism to allow generation firms recover their fixed costs. Various de-rating factors and/or penalties have been incorporated into such mechanisms in order to reward the unit based on the contribution they make to system security, which in turn depends on the unit's reliability. However, this reliability is known to the firm but not to the regulator. We adopt a mechanism design approach for capacity payments based on a declaration by the firm of their reliability. The mechanism scales payments and penalties according to this declared reliability such that the firm's profit-maximising strategy is to truthfully reveal its reliability. A stochastic mixed complementarity problem (MCP) is used to model the interactions between the firms, and we apply this methodology to a test system using Irish electricity market data. Truth-telling is induced, increasing the efficiency of capacity payments while eliminating the requirement for the regulator to allocate resources to discovering reliability.

Suggested Citation

  • Devine, Mel T. & Lynch, Muireann Á., 2017. "Inducing truthful revelation of generator reliability," Energy Economics, Elsevier, vol. 64(C), pages 186-195.
    • Handle: RePEc:eee:eneeco:v:64:y:2017:i:c:p:186-195
    DOI: 10.1016/j.eneco.2017.03.017
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    References listed on IDEAS

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    Cited by:

    1. S. Oliveira, Fernando & William-Rioux, Bertrand & Pierru, Axel, 2023. "Capacity expansion in liberalized electricity markets with locational pricing and renewable energy investments," Energy Economics, Elsevier, vol. 127(PB).

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    More about this item

    Keywords

    Capacity payments; Reliability; Mechanism design; Mixed complementarity problem;
    All these keywords.

    JEL classification:

    • L51 - Industrial Organization - - Regulation and Industrial Policy - - - Economics of Regulation
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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